Klasifikasi Mahasiswa Calon Penerima Beasiswa KIP Menggunakan Algoritma Naive Bayes di Universitas Tomakaka Mamuju
DOI:
https://doi.org/10.37859/jf.v15i3.10784
Abstract
Education is a fundamental aspect of national development that demands equal access to quality education for all. The Smart Indonesia Card (KIP) program is a government initiative aimed at supporting education for underprivileged communities. Tomakaka University, Mamuju, as one of the universities in West Sulawesi, plays an active role in distributing KIP scholarships to students who meet certain criteria. However, the selection process for prospective scholarship recipients has been carried out manually, which may lead to inefficiencies and inaccurate targeting. This study aims to apply the Naïve Bayes algorithm to classify prospective KIP scholarship recipients to make the selection process more objective, fast, and accurate. The research method uses a data mining approach with stages of data preprocessing, dividing training and test data, model training, and testing using the Python programming language on the Google Colab platform. The dataset used is 171 student data, with a division of 75% training data and 25% test data. The test results showed that the Naïve Bayes model achieved an accuracy of 95.35%, with a precision of 97%, a recall of 97%, and a loss of 4.65%, indicating excellent classification performance. Thus, this research contributes to improving administrative efficiency and targeting of KIP scholarship distribution at Tomakaka University, Mamuju.
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